UR's big data research could be big deal for us

The school could secure a leading role is in personalized medicine.

A preliminary rendering of a proposed 50,000-square-foot building adjacent to Hopeman Hall at the University of Rochester. The new building will be home to the Institute for Data Science announced recently.(Photo: Ayers Saint Gross Architects)

The temptation to form premature theories upon insufficient data is the bane of our profession.

— Sherlock Holmes

The University of Rochester recently announced a $50 million commitment to establish itself as a leading academic institution in "big data" research. So is big data the next big deal? It certainly could be. As we have become painfully aware through revelations on the practices of the National Security Agency, never in history has more data been captured and archived. Virtually anything that happens electronically becomes the feedstock for big data research.

Turning data into strategic and actionable information is at the core of the movement. Big data experts in the field of "Predictive Analytics" are emerging, scrambling to be viewed as the thought leaders in this new frontier. Former Columbia University professor Eric Siegel has written the best seller Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has quickly become the layman's primer on the benefits of big data analysis.

How will big data research change how companies market, politicians campaign, and doctors treat patients? In traditional direct marketing to consumers, broad-based approaches are deployed, hoping for a certain "response rate." Big data Predictive Analytics allows companies to analyze massive sets of data and narrow their effort, and costs, to the consumers who "only buy if contacted," a predictive model called uplifting. The same approach is true of politicians in identifying swing voters in swing states.

The most interesting application for big data research and where UR could secure a leading role is in personalized medicine — using enormous amounts of medical data to design predictive models and determine a treatment plan specific to each patient. This would be the Holy Grail of medicine, reducing costs and improving outcomes.

So is $50 million in a building and $2 million in faculty costs going to do it? Not likely, but it is a strong first step. Recruiting internationally renowned scientists and faculty will in large measure determine success. Teaching students proficiency in using the leading analytical software — Hive, Pig, Cassandra and Hadoop, to name a few — will be key.

Nationally, the number of qualified experts using these tools is relatively small. It may make sense to work collaboratively with Rochester Institute of Technology's B. Thomas Golisano College of Computing & Information Sciences, which is recognized nationally for the number of computer scientists it graduates, to create a big data research hub.

Big data research will be where the action is for the next few years and Rochester can certainly emerge as a thought leader and a springboard to commercializing predictive modeling. The competition will be fierce, and the need to get big quickly will allow us to secure a beachhead in the next big thing.